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General Action Video Anomaly Detection On
Metrics
Architecture
Avg. ROC-AUC
Results
Performance results of various models on this benchmark
| Paper Title | Repository | |||
|---|---|---|---|---|
| Pooled Image Level kNN | ViT | 0.58 | Approaches Toward Physical and General Video Anomaly Detection | |
| Video Level features kNN | TimeSformer | 0.52 | Approaches Toward Physical and General Video Anomaly Detection | |
| MNAD | - | 0.52 | Learning Memory-guided Normality for Anomaly Detection |
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